Brain-computer interface (BCI) provides a novel technology for patients and healthy human subjects to control robotic arm. Currently, BCI of arm complete the reaching grasping tasks in an unstructured environment is still challenging because current does not meet requirement manipulating multi-degree accurately robustly. based on steady-state visual evoked potential (SSVEP) could output high information transfer rate; however, conventional SSVEP paradigm failed move continuously users have...

The prolonged calibration time required by steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) poses a significant challenge to real-life applications. Cross-stimulus transfer emerges as promising solution, wherein model trained on subset of classes (seen classes) can predict both seen and unseen classes. Existing approaches extracted common components from SSVEP templates construct for classes; however, they are limited the class-specific activities noise...

Abstract Robotic Endovascular Intervention System (REIS) has been a focused and interesting area in robot‐assisted telesurgery. While, haptic feedback is the latest advancing study interventional robots. Few systems with are commercialized due to accuracy, instantaneity, lack of surgeon previous experience on surgery. In this article, novel force master hand controller system proposed solve problems. A SEA (Series Elastic Actuators)‐based mechanism designed provide high force/torque...

In code-modulated visual evoked potential (c-VEP) based BCI systems, flickering stimuli may result in fatigue. Thus, we introduced a discrete-interval binary sequence (DIBS) as stimulus modulation, with its power spectrum optimized to emphasize high-frequency components (40 Hz-60 Hz). 8 and 17 subjects participated, respectively, offline online experiments on 4-target asynchronous c-VEP-based system designed realize high positive predictive value (PPV), low false rate (FPR) during idle...

The Motor Imagery (MI) paradigm has been widely used in brain-computer interface (BCI) for device control and motor rehabilitation. However, the MI faces challenges such as comprehension difficulty limited decoding accuracy. Therefore, we propose Action Observation with Rhythm (AORI) a natural to provide distinct features high-performance decoding. Twenty subjects were recruited current study perform AORI task. Spectral-spatial, temporal time-frequency analyses conducted investigate...

Decoding different types of movements noninvasively from electroencephalography (EEG) is an essential topic in neural engineering, especially brain-computer interface. Although the widely used sensorimotor rhythm (SMR) efficient limb decoding, it lacks efficacy decoding movement frequencies. Accumulating evidence supports notion that frequency encoded steady-state movement-related (SSMRR). Our study has two primary objectives: firstly, to investigate spatial-spectral representation SSMRR EEG...

While SSVEP-BCI has been widely developed to control external devices, most of them rely on the discrete strategy. The continuous enables users continuously deliver commands and receive real-time feedback from but it suffers transition state problem, a period erroneous recognition, when shift their gazes between targets. To resolve this issue, we proposed novel calibration-free Bayesian approach by hybridizing SSVEP electrooculography (EOG). First, canonical correlation analysis (CCA) was...

Steady-state visual evoked potential (SSVEP) based brain-computer interfaces (BCIs) have achieved an information transfer rate (ITR) of over 300 bits/min, but abundant training data is required. The performance SSVEP algorithms deteriorates greatly under limited data, and the existing time-shift augmentation method fails to improve it because phase-locked requirement between samples violated. To address this issue, study proposes a novel method, namely (PLTS), for SSVEP-BCI. similarity...

Steady-state visual evoked potential (SSVEP) is widely used in the brain-computer interface (BCI) control of external devices due to its high information transfer rate (ITR) and training-free properties. However, SSVEP occupy subjects' channels, it difficult for them perceive actual environment because they can only focus on one stimulus at a time. The typical studies screen show flicker video together. Here, we hypothesize that response could be elicited by moving flickers followed key...

In order to reduce the visual fatigue during use, a high-frequency discrete-interval binary sequence (DIBS) was proposed for an asynchronous 4-target code-modulated evoked potential (c-VEP) brain-computer interface system. However, with traditional spatial filter-based decoding methods, some of subjects have difficulties activating system from idle states, which indicates that system's effectiveness declined because user-specificity. A deep neural network therefore built, consisting two-way...